summ {mStats}

Summary statistics

Description

summ() calculates and displays a variety of summary statistics. If no variables are specified, summary statistics are calculated for all the variables in the dataset.

Usage

summ(data, ..., by = NULL, na.rm = FALSE, digits = 1, detail = FALSE)

Arguments

data

data.frame

...

variable name or names of multiple variables

by

variable name for bivariate analysis

na.rm

logical: if TRUE, it removes observations with missing values.

digits

specify rounding of numbers.

detail

logical: if TRUE, it displays a full spectrum of summary statistics such as inter-quartile range, and p-value from normality test.

Details

It calculates seven number summary statistics, and p-values from relevant statistical tests of association.

ANNOTATIONS

Obs = Number of observations

NA = Number of observations with missing value

Mean = Mean

Std.Dev = Standard deviation

Median = Median value

25% = First quartile or percentile

75% = Third quartile or percentile

Min = Minimum value

Max = Maximum value

Normal = p-value from Shapiro-Wilk Normality Test

Grouped summary statistics

If a strata variable by is specified, grouped summary statistics are calculated. In addition, based on the levels of by, relevant statistical tests of association such as Student's t-test and Wilcoxon, ANOVA and Kruskal-Wallis tests are calculated and their associated p-values are displayed.

Tabulating the whole dataset

This is helpful when the dataset has been processed and finalized. The final dataset can be fed into the function without inputting any variables. This automatically filters and generates tables on variables with possible data types for summary statistics. These data types include numeric, double, integer, and logical.

Using colon : to summarize multiple variables

A colon separator : can be used to summarize variables more efficiently.

Labels

Labels for corresponding variables are displayed below the table.

Value

A list with summ class containing three sets of data.frame type:

1. summary result,

2. summary result without any format,

3. labels for corresponding variables.

Author(s)

Email: [e-mail]

Website: https://myominnoo.github.io/

Examples

## Univariate summary statistics
summ(iris, Sepal.Length)
summ(iris, Sepal.Length:Petal.Width)

## Bivariate summary statistics
summ(iris, Sepal.Length:Petal.Width, by = Species)

## Not run: 
## Using the whole dataset
summ(iris)
summ(iris, by = Species)

## Detailed summary statistics
summ(iris, detail = TRUE)
summ(iris, by = Species, detail = TRUE)

## End(Not run)